Genomic adaptations to cereal-based diets contribute to mitigate metabolic risk in some human populations of East Asian ancestry

Contribution of infectious diseases to the selection of ADH1B and ALDH2 gene variants in Asian populations

BACKGROUND

The gene variants ADH1B*2 (Arg48His, rs1229984) and ALDH2*2 (Glu504Lys, rs671) are common in East Asian populations but rare in other populations. We propose that selective pressures from pathogen exposure and dietary changes during the neolithic transition favored these variants. Thus, their current association with differences in alcohol sensitivity likely results from phenotypic plasticity rather than direct natural selection.

METHODS

Samples sourced from the Allele Frequency Database (ALFRED) were utilized to compute the average frequency of ADH1B*2 and ALDH2*2 across 88 and 61 countries, respectively. Following computation of the average national allele frequencies, we tested the significance of their correlations with ecological variables. Subsequently, we subjected them to Principal Component Analysis (PCA) and Elastic Net regularization. For comprehensive evaluation, we collected individual-level phenotypic associations, compiling a Phenome-Wide Association Study (PheWAS) spanning multiple ethnicities.

RESULTS

Following multiple testing correction, ADH1B*2 displayed significant correlations with Neolithic transition timing (r = 0.405, p.adj = 2.013e-03, n = 57) and historical trypanosome burden (r = -0.418, p.adj = 0.013, n = 57). The first two components of PCA explained 47.7% of the total variability across countries, with the top three contributors being the historical indices of population density and trypanosome and leprosy burdens. Historical burdens of the Mycobacteria tuberculosis and leprosy were the sole predictive variables with positive coefficients that survived Elastic Net regularization.

CONCLUSIONS

Our analyses suggest that Mycobacteria may have played a role in the joint selection of ADH1B*2 and ALDH2*2, expanding the "toxic aldehyde hypothesis" to include Mycobacterium leprae. Additionally, our hypothesis, linked to dietary shifts from rice domestication, emphasizes nutritional deficiencies as a key element in the selective pressure exerted by Mycobacteria. This offers a plausible explanation for the high frequency of ADH1B*2 and ALDH2*2 in Asian populations.

Domestication and the evolution of crops: variable syndromes, complex genetic architectures, and ecological entanglements

Domestication can be considered a specialized mutualism in which a domesticator exerts control over the reproduction or propagation (fitness) of a domesticated species to gain resources or services. The evolution of crops by human-associated selection provides a powerful set of models to study recent evolutionary adaptations and their genetic bases. Moreover, the domestication and dispersal of crops such as rice, maize, and wheat during the Holocene transformed human social and political organization by serving as the key mechanism by which human societies fed themselves. Here we review major themes and identify emerging questions in three fundamental areas of crop domestication research: domestication phenotypes and syndromes, genetic architecture underlying crop evolution, and the ecology of domestication. Current insights on the domestication syndrome in crops largely come from research on cereal crops such as rice and maize, and recent work indicates distinct domestication phenotypes can arise from different domestication histories. While early studies on the genetics of domestication often identified single large-effect loci underlying major domestication traits, emerging evidence supports polygenic bases for many canonical traits such as shattering and plant architecture. Adaptation in human-constructed environments also influenced ecological traits in domesticates such as resource acquisition rates and interactions with other organisms such as root mycorrhizal fungi and pollinators. Understanding the ecological context of domestication will be key to developing resource-efficient crops and implementing more sustainable land management and cultivation practices.

Characterizing the polygenic architecture of complex traits in populations of East Asian and European descent

To investigate the polygenicity of complex traits in populations of East Asian (EAS) and European (EUR) descents, we leveraged genome-wide data from Biobank Japan, UK Biobank, and FinnGen cohorts. Specifically, we analyzed up to 215 outcomes related to 18 health domains, assessing their polygenic architecture via descriptive statistics, such as the proportion of susceptibility SNPs per trait (πc). While we did not observe EAS-EUR differences in the overall distribution of polygenicity parameters across the phenotypes investigated, there were ancestry-specific patterns in the polygenicity differences between health domains. In EAS, pairwise comparisons across health domains showed enrichment for πc differences related to hematological and metabolic traits (hematological fold-enrichment = 4.45, p = 2.15 × 10-7; metabolic fold-enrichment = 4.05, p = 4.01 × 10-6). For both categories, the proportion of susceptibility SNPs was lower than that observed for several other health domains (EAS-hematological median πc = 0.15%, EAS-metabolic median πc = 0.18%) with the strongest πc difference with respect to respiratory traits (EAS-respiratory median πc = 0.50%; hematological-p = 2.26 × 10-3; metabolic-p = 3.48 × 10-3). In EUR, pairwise comparisons showed multiple πc differences related to the endocrine category (fold-enrichment = 5.83, p = 4.76 × 10-6), where these traits showed a low proportion of susceptibility SNPs (EUR-endocrine median πc = 0.01%) with the strongest difference with respect to psychiatric phenotypes (EUR-psychiatric median πc = 0.50%; p = 1.19 × 10-4). Simulating sample sizes of 1,000,000 and 5,000,000 individuals, we also showed that ancestry-specific polygenicity patterns translate into differences across health domains in the genetic variance explained by susceptibility SNPs projected to be genome-wide significant (e.g., EAS hematological-neoplasm p = 2.18 × 10-4; EUR endocrine-gastrointestinal p = 6.80 × 10-4). These findings highlight that traits related to the same health domains may present ancestry-specific variability in their polygenicity.

Genome-wide scans for selective sweeps using convolutional neural networks

MOTIVATION

Recent methods for selective sweep detection cast the problem as a classification task and use summary statistics as features to capture region characteristics that are indicative of a selective sweep, thereby being sensitive to confounding factors. Furthermore, they are not designed to perform whole-genome scans or to estimate the extent of the genomic region that was affected by positive selection; both are required for identifying candidate genes and the time and strength of selection.

RESULTS

We present ASDEC (https://github.com/pephco/ASDEC), a neural-network-based framework that can scan whole genomes for selective sweeps. ASDEC achieves similar classification performance to other convolutional neural network-based classifiers that rely on summary statistics, but it is trained 10× faster and classifies genomic regions 5× faster by inferring region characteristics from the raw sequence data directly. Deploying ASDEC for genomic scans achieved up to 15.2× higher sensitivity, 19.4× higher success rates, and 4× higher detection accuracy than state-of-the-art methods. We used ASDEC to scan human chromosome 1 of the Yoruba population (1000Genomes project), identifying nine known candidate genes.

Characterizing the polygenic architecture of complex traits in populations of East Asian and European descent

To investigate the polygenicity of complex traits in populations of East Asian (EAS) and European (EUR) descents, we leveraged genome-wide data from Biobank Japan, UK Biobank, and FinnGen cohorts. Specifically, we analyzed up to 215 outcomes related to 18 health domains, assessing their polygenic architecture via descriptive statistics, such as the proportion of susceptibility SNPs per trait (π _c ). While we did not observe EAS-EUR differences in the overall distribution of polygenicity parameters across the phenotypes investigated, there were ancestry-specific patterns in the polygenicity differences between health domains. In EAS, pairwise comparisons across health domains showed enrichment for π _c differences related to hematological and metabolic traits (hematological fold-enrichment=4.45, p=2.15×10 ^-7 ; metabolic fold-enrichment=4.05, p=4.01×10 ^-6 ). For both categories, the proportion of susceptibility SNPs was lower than that observed for several other health domains (EAS-hematological median π _c =0.15%, EAS-metabolic median π _c =0.18%) with the strongest π _c difference with respect to respiratory traits (EAS-respiratory median π _c =0.50%; Hematological-p=2.26×10 ^-3 ; Metabolic-p=3.48×10 ^-3 ). In EUR, pairwise comparisons showed multiple π _c differences related to the endocrine category (fold-enrichment=5.83, p=4.76×10 ^-6 ), where these traits showed a low proportion of susceptibility SNPs (EUR-endocrine median π _c =0.01%) with the strongest difference with respect to psychiatric phenotypes (EUR-psychiatric median π _c =0.50%; p=1.19×10 ^-4 ). Simulating sample sizes of 1,000,000 and 5,000,000 individuals, we also showed that ancestry-specific polygenicity patterns translate into differences across health domains in the genetic variance explained by susceptibility SNPs projected to be genome-wide significant (e.g., EAS hematological-neoplasm p=2.18×10 ^-4 ; EUR endocrine-gastrointestinal p=6.80×10 ^-4 ). These findings highlight that traits related to the same health domains may present ancestry-specific variability in their polygenicity.

Inferring Signatures of Positive Selection in Whole-Genome Sequencing Data: An Overview of Haplotype-Based Methods

Signatures of positive selection in the genome are a characteristic mark of adaptation that can reveal an ongoing, recent, or ancient response to environmental change throughout the evolution of a population. New sources of food, climate conditions, and exposure to pathogens are only some of the possible sources of selective pressure, and the rise of advantageous genetic variants is a crucial determinant of survival and reproduction. In this context, the ability to detect these signatures of selection may pinpoint genetic variants that are responsible for a significant change in gene regulation, gene expression, or protein synthesis, structure, and function. This review focuses on statistical methods that take advantage of linkage disequilibrium and haplotype determination to reveal signatures of positive selection in whole-genome sequencing data, showing that they emerge from different descriptions of the same underlying event. Moreover, considerations are provided around the application of these statistics to different species, their suitability for ancient DNA, and the usefulness of discovering variants under selection for biomedicine and public health in an evolutionary medicine framework.

Dietary, Cultural and Pathogens-Related Selective Pressures Shaped Differential Adaptive Evolution Among Native Mexican Populations

Native American genetic ancestry has been remarkably implicated with increased risk of diverse health issues in several Mexican populations, especially in relation to the dramatic changes in environmental, dietary, and cultural settings they have recently undergone. In particular, the effects of these ecological transitions and Westernization of lifestyles have been investigated so far predominantly on Mestizo individuals. Nevertheless, indigenous groups, rather than admixed Mexicans, have plausibly retained the highest proportions of genetic components shaped by natural selection in response to the ancient milieu experienced by Mexican ancestors during their pre-Columbian evolutionary history. These formerly adaptive variants have the potential to represent the genetic determinants of some biological traits that are peculiar to Mexican people, as well as a reservoir of loci with possible biomedical relevance. To test such a hypothesis, we used genome-wide genotype data to infer the unique adaptive evolution of Native Mexican groups selected as reasonable descendants of the main pre-Columbian Mexican civilizations. A combination of haplotype-based and gene-network analyses enabled us to detect genomic signatures ascribable to polygenic adaptive traits plausibly evolved by the main genetic clusters of Mexican indigenous populations to cope with local environmental and/or cultural conditions. Some of these adaptations were found to play a role in modulating the susceptibility/resistance of these groups to certain pathological conditions, thus providing new evidence that diverse selective pressures have contributed to shape the current biological and disease-risk patterns of present-day Native and Mestizo Mexican populations.

Dietary Carbohydrate and Diverse Health Outcomes: Umbrella Review of 30 Systematic Reviews and Meta-Analyses of 281 Observational Studies

Background and Aims: The associations between dietary carbohydrate and diverse health outcomes remain controversial and confusing. To summarize the existing evidence of the association between dietary carbohydrate intake and diverse health outcomes and to evaluate the credibility of these sources of evidence. We performed this umbrella review of evidence from meta-analyses of observational studies.

Methods: PubMed, Embase, Web of Science databases, and manual screening of references up to July 2020 were searched. Systematic reviews with meta-analyses of observational studies in humans investigating the association between dietary carbohydrate intake and multiple health outcomes were identified. We assessed the evidence levels by using summary effect sizes, 95% prediction intervals, between-study heterogeneity, evidence of small-study effects, and evidence of excess significance bias for each meta-analysis.

Results: We included 43 meta-analyses of observational research studies with 23 health outcomes, including cancer (n = 26), mortality (n = 4), metabolic diseases (n = 4), digestive system outcomes (n = 3), and other outcomes [coronary heart disease (n = 2), stroke (n = 1), Parkinson's disease (n = 1), and bone fracture (n = 2)]. This umbrella review summarized 281 individual studies with 13,164,365 participants. Highly suggestive evidence of an association between dietary carbohydrate intake and metabolic syndrome was observed with adjusted summary odds ratio of 1.25 [95% confidence interval (CI) 1.15–1.37]. The suggestive evidences were observed in associations of carbohydrate consumption with esophageal adenocarcinoma (0.57, 95% CI = 0.42–0.78) and all-cause mortality (adjusted summary hazard ratio 1.19, 95% CI = 1.09–1.30).

Conclusions: Despite the fact that numerous systematic reviews and meta-analyses have explored the relationship between carbohydrate intake and diverse health outcomes, there is no convincing evidence of a clear role of carbohydrate intake. However, there is highly suggestive evidence suggested carbohydrate intake is associated with high risk of metabolic syndrome, suggestive evidence found its association with increased risk of all-cause mortality and decreased risk of esophageal adenocarcinoma.

Systematic Review Registration: CRD42020197424.